Search ga_ls8c_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. to (exclusive):

Time when dataset was created (processed) From

Time when dataset was created (processed) to (exclusive)

The raw CRS string as it appears in metadata:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. from:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm to (exclusive):

File format (GeoTiff, NetCDF):

GQA Circular error probable (90%) from:

GQA Circular error probable (90%) to (exclusive):

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Dataset UUID:

User who indexed the dataset:

When dataset was indexed:

Label:

A Landsat Collection 1 Level-1 product identifier including the Collection processing levels, processing date, collection number, and collection tier category (e.g. ‘LE07_L1TP_098084_20210307_20210308_02_RT’) :

A Landsat scene ID including WRS path and row, year and day, ground station identifier and archive version number (e.g. ‘LC80900852021066LGN00’) :

Latitude range from:

Latitude range to (exclusive):

Longitude range from:

Longitude range to (exclusive):

Full metadata document:

Metadata type name of dataset:

ID of a metadata type:

Spatial reference code from the provider. For Landsat region_code is a scene path row: '{:03d}{:03d}.format(path,row)' For Sentinel it is MGRS code. In general it is a unique string identifier that datasets covering roughly the same spatial region share. :

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2022-11-05 10:11:46	ga_ls8c_ard_3-2-1_099072_2022-11-05_final
2022-11-06 10:56:13	ga_ls8c_ard_3-2-1_106075_2022-11-06_final
2022-11-08 10:42:15	ga_ls8c_ard_3-2-1_104071_2022-11-08_final
2022-11-08 10:42:39	ga_ls8c_ard_3-2-1_104072_2022-11-08_final
2022-11-14 10:07:06	ga_ls8c_ard_3-2-1_098076_2022-11-14_final
2022-11-16 09:53:07	ga_ls8c_ard_3-2-1_096072_2022-11-16_final
2022-11-21 10:12:51	ga_ls8c_ard_3-2-1_099075_2022-11-21_final
2022-11-22 09:18:26	ga_ls8c_ard_3-2-1_090078_2022-11-21_final
2022-11-22 09:20:02	ga_ls8c_ard_3-2-1_090082_2022-11-21_final
2022-11-22 10:58:07	ga_ls8c_ard_3-2-1_106080_2022-11-22_final
2022-11-23 11:42:11	ga_ls8c_ard_3-2-1_113082_2022-11-23_final
2022-11-25 09:47:45	ga_ls8c_ard_3-2-1_095074_2022-11-25_final
2022-11-26 10:30:37	ga_ls8c_ard_3-2-1_102073_2022-11-26_final
2022-11-30 10:05:30	ga_ls8c_ard_3-2-1_098072_2022-11-30_final
2022-11-30 10:05:54	ga_ls8c_ard_3-2-1_098073_2022-11-30_final
2022-12-01 10:47:58	ga_ls8c_ard_3-2-1_105070_2022-12-01_final
2022-12-02 09:53:33	ga_ls8c_ard_3-2-1_096073_2022-12-02_final
2022-12-02 09:57:32	ga_ls8c_ard_3-2-1_096083_2022-12-02_final
2022-12-03 10:36:24	ga_ls8c_ard_3-2-1_103072_2022-12-03_final
2022-12-04 11:19:40	ga_ls8c_ard_3-2-1_110072_2022-12-04_final
2022-12-12 10:31:23	ga_ls8c_ard_3-2-1_102075_2022-12-12_final
2022-12-12 10:32:35	ga_ls8c_ard_3-2-1_102078_2022-12-12_final
2022-12-13 09:40:08	ga_ls8c_ard_3-2-1_093086_2022-12-13_final
2022-12-13 11:13:50	ga_ls8c_ard_3-2-1_109073_2022-12-13_final
2022-12-15 09:24:58	ga_ls8c_ard_3-2-1_091079_2022-12-14_final
2022-12-16 10:07:25	ga_ls8c_ard_3-2-1_098077_2022-12-16_final
2022-12-17 09:12:59	ga_ls8c_ard_3-2-1_089080_2022-12-16_final
2022-12-17 10:47:52	ga_ls8c_ard_3-2-1_105070_2022-12-17_final
2022-12-19 10:34:41	ga_ls8c_ard_3-2-1_103068_2022-12-19_final
2022-12-19 10:35:53	ga_ls8c_ard_3-2-1_103071_2022-12-19_final
2022-12-20 09:41:50	ga_ls8c_ard_3-2-1_094075_2022-12-20_final
2022-12-20 09:44:38	ga_ls8c_ard_3-2-1_094082_2022-12-20_final
2022-12-20 11:23:07	ga_ls8c_ard_3-2-1_110081_2022-12-20_final
2022-12-22 09:33:50	ga_ls8c_ard_3-2-1_092086_2022-12-22_final
2022-12-22 09:35:02	ga_ls8c_ard_3-2-1_092089_2022-12-22_final
2022-12-24 10:57:58	ga_ls8c_ard_3-2-1_106080_2022-12-24_final
2022-12-25 11:39:38	ga_ls8c_ard_3-2-1_113076_2022-12-25_final
2022-12-25 11:40:50	ga_ls8c_ard_3-2-1_113079_2022-12-25_final
2022-12-27 09:52:48	ga_ls8c_ard_3-2-1_095087_2022-12-27_final
2022-12-31 09:25:41	ga_ls8c_ard_3-2-1_091081_2022-12-30_final
2022-12-31 09:26:05	ga_ls8c_ard_3-2-1_091082_2022-12-30_final
2022-12-31 09:26:29	ga_ls8c_ard_3-2-1_091083_2022-12-30_final
2022-12-31 11:03:47	ga_ls8c_ard_3-2-1_107079_2022-12-31_final
2023-01-01 11:45:27	ga_ls8c_ard_3-2-1_114075_2023-01-01_final
2023-01-02 09:12:08	ga_ls8c_ard_3-2-1_089078_2023-01-01_final
2023-01-02 09:14:56	ga_ls8c_ard_3-2-1_089085_2023-01-01_final
2023-01-02 09:15:20	ga_ls8c_ard_3-2-1_089086_2023-01-01_final
2023-01-05 11:20:43	ga_ls8c_ard_3-2-1_110075_2023-01-05_final
2023-01-07 11:05:57	ga_ls8c_ard_3-2-1_108069_2023-01-07_final
2023-01-07 11:07:57	ga_ls8c_ard_3-2-1_108074_2023-01-07_final
2023-01-08 10:11:31	ga_ls8c_ard_3-2-1_099072_2023-01-08_final
2023-01-08 10:15:55	ga_ls8c_ard_3-2-1_099083_2023-01-08_final
2023-01-08 11:51:36	ga_ls8c_ard_3-2-1_115075_2023-01-08_final
2023-01-10 09:58:21	ga_ls8c_ard_3-2-1_097070_2023-01-10_final
2023-01-10 10:03:32	ga_ls8c_ard_3-2-1_097083_2023-01-10_final
2023-01-10 11:40:01	ga_ls8c_ard_3-2-1_113077_2023-01-10_final
2023-01-11 10:44:47	ga_ls8c_ard_3-2-1_104078_2023-01-11_final
2023-01-12 11:29:14	ga_ls8c_ard_3-2-1_111081_2023-01-12_final
2023-01-19 09:56:52	ga_ls8c_ard_3-2-1_096082_2023-01-19_final
2023-01-19 09:57:16	ga_ls8c_ard_3-2-1_096083_2023-01-19_final
2023-01-22 10:26:37	ga_ls8c_ard_3-2-1_101079_2023-01-22_final
2023-01-23 09:29:24	ga_ls8c_ard_3-2-1_092075_2023-01-22_final
2023-01-23 09:34:12	ga_ls8c_ard_3-2-1_092087_2023-01-23_final
2023-01-23 11:08:17	ga_ls8c_ard_3-2-1_108075_2023-01-23_final
2023-01-24 10:13:04	ga_ls8c_ard_3-2-1_099076_2023-01-24_final
2023-01-24 10:16:40	ga_ls8c_ard_3-2-1_099085_2023-01-24_final
2023-01-25 09:20:39	ga_ls8c_ard_3-2-1_090084_2023-01-24_final
2023-01-25 09:21:03	ga_ls8c_ard_3-2-1_090085_2023-01-24_final
2023-01-25 10:57:09	ga_ls8c_ard_3-2-1_106078_2023-01-25_final
2023-01-25 10:57:32	ga_ls8c_ard_3-2-1_106079_2023-01-25_final
2023-01-26 10:00:20	ga_ls8c_ard_3-2-1_097075_2023-01-26_final
2023-01-29 10:30:27	ga_ls8c_ard_3-2-1_102073_2023-01-29_final
2023-01-30 09:39:37	ga_ls8c_ard_3-2-1_093085_2023-01-30_final
2023-01-30 09:40:25	ga_ls8c_ard_3-2-1_093087_2023-01-30_final
2023-01-31 10:17:41	ga_ls8c_ard_3-2-1_100072_2023-01-31_final
2023-02-01 09:26:51	ga_ls8c_ard_3-2-1_091084_2023-01-31_final
2023-02-06 11:23:04	ga_ls8c_ard_3-2-1_110081_2023-02-06_final
2023-02-07 10:26:38	ga_ls8c_ard_3-2-1_101079_2023-02-07_final
2023-02-10 09:22:37	ga_ls8c_ard_3-2-1_090089_2023-02-09_final
2023-02-14 10:29:57	ga_ls8c_ard_3-2-1_102072_2023-02-14_final
2023-02-15 11:12:00	ga_ls8c_ard_3-2-1_109069_2023-02-15_final
2023-02-15 11:17:59	ga_ls8c_ard_3-2-1_109084_2023-02-15_final
2023-02-17 09:27:54	ga_ls8c_ard_3-2-1_091087_2023-02-16_final
2023-02-18 11:46:02	ga_ls8c_ard_3-2-1_114077_2023-02-18_final
2023-02-20 09:57:09	ga_ls8c_ard_3-2-1_096083_2023-02-20_final
2023-02-22 11:18:26	ga_ls8c_ard_3-2-1_110070_2023-02-22_final
2023-02-22 11:22:49	ga_ls8c_ard_3-2-1_110081_2023-02-22_final
2023-02-22 11:23:37	ga_ls8c_ard_3-2-1_110083_2023-02-22_final
2023-02-23 10:23:11	ga_ls8c_ard_3-2-1_101071_2023-02-23_final
2023-02-23 10:25:11	ga_ls8c_ard_3-2-1_101076_2023-02-23_final
2023-02-25 10:12:46	ga_ls8c_ard_3-2-1_099076_2023-02-25_final
2023-02-27 11:40:30	ga_ls8c_ard_3-2-1_113079_2023-02-27_final
2023-02-27 11:42:06	ga_ls8c_ard_3-2-1_113083_2023-02-27_final
2023-02-28 09:06:24	ga_ls8c_ard_3-2-1_088080_2023-02-27_final
2023-03-01 11:29:20	ga_ls8c_ard_3-2-1_111082_2023-03-01_final
2023-03-05 09:26:06	ga_ls8c_ard_3-2-1_091083_2023-03-04_final
2023-03-05 09:27:18	ga_ls8c_ard_3-2-1_091086_2023-03-04_final
2023-03-05 11:00:12	ga_ls8c_ard_3-2-1_107071_2023-03-05_final
2023-03-06 11:45:50	ga_ls8c_ard_3-2-1_114077_2023-03-06_final
2023-03-11 10:23:04	ga_ls8c_ard_3-2-1_101071_2023-03-11_final

Return to ga_ls8c_ard_3 whole collection overview

ga_ls8c_ard_3: Geoscience Australia Landsat 8 Operational Land Imager and Thermal Infra-Red Scanner Analysis Ready Data Collection 3

Baseline satellite data

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years